Diagnostic tests that can be performed at the point of care of an individual, such as at the bedside of a patient, at a care provider location, or at the home of the patient, are becoming increasingly popular. Diagnostic tests include tests directed to identifying biomarkers such as Nucleic Acid, protein, and small molecules. Many of the diagnostic testing devices incorporate affinity based sensors which are considered to be the state-of-the-art in detection of biomarkers.
Affinity based biosensors function according to a “key-lock” principal in which a molecule with very high association factor to the biomarker of interest is used for detection. For example, a pregnancy test kit may incorporate a monoclonal antibody specific to a β-subunit of hCG (βhCG). The antibody is conjugated with a tag, e.g., gold, latex, or fluorophore, which is used for detection. If the targeted molecule binds with the conjugated antibody, the tagged key-lock pair will be detectable such as by a visible test line.
ELISA plates and microarrays (e.g., Nucleic Acid, peptide, and protein) incorporate a similar principal. FIG. 1 depicts an ELISA assay 10 wherein antibodies 12 are immobilized on a substrate 14. The substrate 14 may be positioned within a well (not shown). A blocker 16 is provided to cover the surface of the substrate around the antibody 12. In a typical ELISA assay, a sample including molecules of interest 18 is then added to the well in which the primary antibody 12 is immobilized. Next, the sample is incubated for some time. During incubation, the blocker 16 prevents the molecules of interest in the sample from binding to the surface of the substrate 14 in order to avoid false binding. During incubation, some of the molecules of interest 18 become bound with some of the antibodies 12 as depicted in FIG. 2. After incubation, the remaining sample is washed to remove the unbound molecules of interest 18.
Subsequently, a secondary antibody 20 with a bound label 22 is added to the well, incubated, and washed resulting in the configuration of FIG. 3. As depicted in FIG. 3, the labeled secondary antibodies 20 are bound to the molecules of interest 18 that are in turn bound to the antibodies 12. Accordingly, the number of labels 22 bound by the antibodies 20 to the molecules of interest 18 is proportional to the concentration of the target antigen. Depending on the label used, the number of labels can be finally detected using colorimetry, amperometry, magnetometry, voltammetry, luminescence, or fluorescence detection. Other label-free antibody processes such as surface plasmon resonance may alternatively be used.
The two main figures-of-merit in a detection assay include sensitivity and cross-reactivity; both of which affect the minimum detectable concentration and the diagnosis error rate. The sensitivity in such tests is generally limited by label detection accuracy, association factor of the antibody-antigen pair, and the effective density of the probe antibody on the surface.
One issue that arises with affinity based sensors is the cross-reactivity of the sensor to other biomarkers. In other words, rather than sensing a single biomarker or molecule of interest, a sensor tends to also sense biomarkers other than the biomarker of interest. The cross-reactivity issue is depicted in FIG. 4 wherein an ELISA assay 30 includes antibodies 32 immobilized on a substrate 34 with a blocker 36 coating most of the surface of the substrate 32. Additionally, a labeled secondary antibody 38 is bound to a molecule of interest 40 which is in turn bound by the primary antibody 32. The labeled secondary antibody 38 has also bound to a molecule 42 which exhibited an affinity for the primary antibody 32 and to the labeled secondary antibody 38. The sensitivity to a broad range of biomarkers thus increases the false negative/positive rate of diagnostic tests at clinical level as reported, for example, by P. A Benn et al., “Estimates for the sensitivity and false-positive rates for second trimester serum screening for Down syndrome and trisomy 18 with adjustment for cross identification and doublepositive results,” Prenatal Diagnosis, Vol. 21, No. 1, pp 46-51, 2001. The presence of other molecules (secondary molecules or antigens) in the sample thus affects the minimum detectable concentration by binding to the primary antibody.
The accuracy of the assay may further be affected by physiosorption. As further depicted in FIG. 4, some features 44 present in the ELISA assay 30, either contaminants or simply an incongruity, may also be bound to a labeled secondary antibody 38. The physiosorbed labeled secondary antibody 38 thus causes an increased background signal.
In an effort to mitigate the various sensitivity and interference issues involved with affinity based testing, a particular assay is typically optimized by finding a combination of reagents and environmental conditions that maximizes the binding of the molecule of interest to the antibody. Thus, optimization can entail incorporating highly selective antibodies.
Overcoming the cross-reactivity and background problems can significantly delay development of a new assay test and can increase the cost and complexity of the overall test. For example a typical development of an ELISA assay requires several scientists working for more than a year to identify an acceptable antibody. Cross-reactivity of proteins is a common source of the failure of such development efforts.
The issue of broad biomarker sensitivity can also be mitigated by incorporating a number of different affinity based sensors into a test device and then determining the relative concentrations of biomarkers. This approach, however, increases the cost of manufacturing the test device and the costs associated with processing the test device.
A need exists for a device and method of performing an assay incorporating low cost antibodies. A further need exists for low cost assays including multiplexed assays, protein arrays, lateral flow devices, sandwich assays, competitive assays, or bead based arrays which provide accurate results and a method of using such arrays. Methods and devices which provide more accurate results than so-called optimized assays would be a further benefit.